Artificial Intelligence in Science
Challenges, Opportunities and the Future of Research
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The rapid advances of artificial intelligence (AI) in recent years have led to numerous creative applications in science. Accelerating the productivity of science could be the most economically and socially valuable of all the uses of AI. Utilising AI to accelerate scientific productivity will support the ability of OECD countries to grow, innovate and meet global challenges, from climate change to new contagions.
This publication is aimed at a broad readership, including policy makers, the public, and stakeholders in all areas of science. It is written in non-technical language and gathers the perspectives of prominent researchers and practitioners. The book examines various topics, including the current, emerging, and potential future uses of AI in science, where progress is needed to better serve scientific advancements, and changes in scientific productivity.
Additionally, it explores measures to expedite the integration of AI into research in developing countries.
A distinctive contribution is the book’s examination of policies for AI in science. Policy makers and actors across research systems can do much to deepen AI’s use in science, magnifying its positive effects, while adapting to the fast-changing implications of AI for research governance.
From knowledge discovery to knowledge creation: How can literature-based discovery accelerate progress in science?
This essay gives an overview and describes prospects for generating new scientific knowledge from disparate datasets, as viewed by four active practitioners from around the globe (Illinois, Arizona, Slovenia and Australia). Although artificial intelligence (AI) and machine learning (ML) are central techniques employed in the field, the key concepts in this essay are undiscovered public knowledge (UPK) and literature-based discovery (LBD). These comprise a variety of situations, including some not yet tackled via ML.
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